Skip to main content
Research project

my Smart COPD exacerbation management

Project overview

Project Vision

Chronic obstructive pulmonary disease (COPD) is a common disease and is predicted to become the 3rd leading cause of death by 2030. Because there is no cure, treatment involves long-term management of symptoms to slow the decline of patient health and improve quality of life. A key characteristic of COPD is the presence of ‘exacerbation events’ defined as an acute worsening of symptoms. Exacerbation events are detrimental to health and often lead to hospitalization. Avoiding exacerbation events leads to a higher quality of and longer life.

Project Objectives

Our plan has four work packages addressing clinical, technical, modelling and adoption objectives. In WP1 “Person Centred Care” we will create the patient journey and clinical model working with clinicians, patients, and members of the public. WP1 will also validate the application in a clinical trial to ensure it is safe and effective. In WP2 “Agile Digital Platform Engineering”, we will extend the nationally available NHS myCOPD application with intelligent computer algorithms from a dedicated WP3 “Predictive Analytics and Visualisation”. Finally, WP4 “Dissemination, Certification and NHS Adoption” will engage stakeholders, obtain regulatory approvals, and secure further investment. Patient and public involvement has been an integral part of the myCOPD app and mySmartCOPD proposal development.

PPI will continue in this project through co-creation, testing and evaluation activities from concept through to clinical trial. PPI will influence data collection, data usage, clinical model, and user interfaces. PPI will allow the evaluation of trust, adoption, and behavioural change. PPI will inform features and priorities for the clinical trial. Existing patients from the myCOPD digital health ecosystem will participate directly in the trial.

The objectives of the project are:

* Objective 1: Develop a safe and reliable AI pipeline and components for prediction of COPD exacerbation events within the myCOPD digital health platform
* Objective 2: Ensure mySmartCOPD is as acceptable and engaging (and effective) as possible for patients and clinicians
* Objective 3: Objective 3: Establish evidence for clinical efficacy data, safety data, regulatory data (WP3) necessary for CE/UKCA marking and entry into Phase 3 “Real World Testing”.
* Objective 4: Establish a competitive AI-enhanced digital health ecosystem for management of COPD delivering economic value and building on strong commercial and NHS partnerships

Our goal is to provide a new way of managing COPD by using computers to predict exacerbation events several days in advance. A recent feasibility study we ran demonstrated that using a technique called artificial intelligence (AI), computers could learn when patients were likely to exacerbate from reported symptoms, lifestyle, and demographic data. By providing an early warning, people with COPD have an opportunity to take action to prevent an exacerbation or lessen its severity. Consequently, we expect that patients will have more control over their condition, medication will be used more appropriately and allow more efficient use of NHS resources.


Lead researcher

Professor Michael Boniface CEng, FIET

Professorial Fellow in Information Techn

Research interests

  • Artifical intelligence for health systems
  • Human centred interactive systems
  • Federated systems management 
Connect with Michael
Other researchers

Professor Andrew Cook MBBS MPH FFPH

Professorial Fellow in HTA

Research interests

  • Pragmatic Clinical Trials
  • Research Conduct
  • Guidelines
Connect with Andrew

Research outputs